The hippocampus is a brain region involved in higher cognitive functions, such as learning and memory, and is often affected by important neurological illnesses like epilepsy, schizophrenia and Alzheimer's disease. GABAergic interneurons of the hippocampus display a wide anatomical and functional diversity. Distinct types of interneurons innervate specific postsynaptic domains such as the axon initial segment, soma, as well as the proximal and distal dendrites of principal neurons. This anatomical specificity has been suggested to relate to different functional roles. Most interneurons have been studied "in vitro" during static network conditions, that is to say, from quiescent slices that lack the type of circuitry activity that is likely to occur "in vivo." As a consequence, the interactions between GABAergic interneurons and specific postsynaptic target domains during physiologically- or pathologically-relevant states of the network are not well understood. Therefore, the primary goal of this research is to re-evaluate the functional roles of interneuron diversity and GABAergic input domain specificity during activity similar to rhythms occurring "in vivo" in the brain. We will study the role of interneuron diversity and domain specific GABAergic input during hippocampal synchronous bursting, which is related to higher cognitive activity in the normal brain, but can progress to pathological levels in epileptic conditions. We will focus our project on three specific aims: (i) we will test the hypothesis that perisomatic and dendritic GABAergic inputs regulate different network functions, (ii) we will test the hypothesis that network-driven bursting in individual pyramidal cells can be controlled by specific sets of interneurons, and, finally, (iii) we will test the hypothesis that synaptic properties of specific sets of interneurons control the timing of GABAergic input during network activity. Relating different interneurons and GABAergic inputs to clear functions may lead to important insight into the organizing principles of cortical networks in the normal brain and during disease.